Long_Term_Memory_MCP_Server / demo_script.md
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A newer version of the Gradio SDK is available: 6.26.0

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🎬 Demo Script & Testing Guide

Quick Start Testing

1. Test Gradio Interface

  1. Visit the Hugging Face Space
  2. Try saving a memory in the "Save Memory" tab
  3. Search for it in the "Search Memory" tab
  4. Browse all memories in the "Browse Memories" tab

2. Test MCP Server with Claude Desktop

Setup:

  1. Add to your claude_desktop_config.json:
{
  "mcpServers": {
    "long-term-memory": {
      "command": "python",
      "args": ["run_mcp_server.py"],
      "env": {},
      "cwd": "/path/to/your/project"
    }
  }
}
  1. Restart Claude Desktop

Demo Scenarios

Scenario 1: Philosophy Student

  1. Save insights from reading different philosophers
  2. Search for connections between ideas
  3. Build upon previous understanding in new discussions

Scenario 2: Research Notes

  1. Save key findings from papers
  2. Find related research using semantic search
  3. Synthesize knowledge across sessions

Scenario 3: Personal Development

  1. Save insights from conversations about goals
  2. Track progress and learnings over time
  3. Reference past conclusions in future planning

Testing Checklist

Basic Functionality

  • Save memory with all fields
  • Save memory with minimal fields
  • Search with various queries
  • Search with different thresholds
  • List memories with different limits
  • View memory statistics

Edge Cases

  • Empty search query
  • Search with no results
  • Search when no memories exist
  • Very long content
  • Special characters in content
  • Multiple identical memories

MCP Integration

  • Server starts correctly
  • Tools are discovered by client
  • All tools execute successfully
  • Error handling works
  • Multiple concurrent requests

Performance Benchmarks

Expected Performance

  • Save Memory: < 1 second
  • Search 100 memories: < 2 seconds
  • List memories: < 0.5 seconds
  • Memory footprint: ~50MB for 1000 memories

Scalability Limits

  • ChromaDB: Handles 100K+ documents efficiently
  • Embeddings: 384-dimensional vectors (all-MiniLM-L6-v2)
  • Storage: ~1KB per memory average

Troubleshooting

Common Issues

  1. "MCP not available": Install missing dependencies
  2. Embedding model fails: Check internet connection for initial download
  3. ChromaDB errors: Check write permissions for memory_db directory
  4. Claude Desktop not connecting: Verify config.json path an